13 papers · ranked by Valyu relevance
S. Gopi, Prabhujit Mohapatra
In recent years, many researchers have made a continuous effort to develop new and efficient meta-heuristic algorithms to address complex problems. Hence, in this study, a novel human-based meta-heuristic algorithm, namely, the learning cooking algorithm (LCA), is proposed that mimics the cooking learning activity of…
Iker Azurmendi, Ekaitz Zulueta, Jose Manuel Lopez-Guede, Jon Azkarate + 2 more
'Jon Azkarate' 'Manuel González' 'Alessandro Leone'] Deep Learning (DL) has provided a significant breakthrough in many areas of research and industry. The development of Convolutional Neural Networks (CNNs) has enabled the improvement of computer vision-based techniques, making the information gathered from cameras…
Eva Trojovská, Mohammad Dehghani
Metaheuristic algorithms have a wide range of applications in handling optimization problems. In this study, a new metaheuristic algorithm, called the chef-based optimization algorithm (CBOA), is developed. The fundamental inspiration employed in CBOA design is the process of learning cooking skills in training…
Ganesh Bagler, Mansi Goel
Cooking, a quintessential creative pursuit, holds profound significance for individuals, communities, and civilizations. Food and cooking transcend mere sensory pleasure to influence nutrition and public health outcomes. Inextricably linked to culinary and cultural heritage, food systems play a pivotal role in…
Chakradhar Reddy Nallu
This paper is based on developing different algorithms, which generate the task tree planning for the given goal node(recipe). The knowledge representation of the dishes is called FOON. It contains the different objects and their between them with respective to the motion node The graphical representation of FOON is…
Eduardo C. Garrido-Merchán, Alejandro Albarca-Molina
> Abstract. Cooking typically involves a plethora of decisions about ingredients and tools that need to be chosen in order to write a good cooking recipe. Cooking can be modelled in an optimization framework, as it involves a search space of ingredients, kitchen tools, cooking times or temperatures. If we model as an…
Yuan Wang, Bin Xhu, Yanbin Hao, Chong‐Wah Ngo + 2 more
Diffusion Authors: ['Yuan Wang' 'Bin Xhu' 'Yanbin Hao' 'Chong‐Wah Ngo' 'Yi Tan' 'Xiang Wang'] Recent advancements in text-to-image generation models have excelled in creating diverse and realistic images. This success extends to food imagery, where various conditional inputs like cooking styles, ingredients, and…
Primož Podržaj, Dominik Kozjek, Gašper Škulj, Tomaž Požrl + 2 more
This paper presents a novel approach to thermal process control in the food industry, specifically targeting the pasteurization and cooking of soft-boiled eggs. The unique challenge of this process lies in the precise temperature control required, as pasteurization and cooking must occur within a narrow temperature…
Tibet Duman, Ekrem Duman
In this study, we first introduce a new application of the asymmetric traveling salesman problem (ATSP) which is about a small restaurant with one cook and a single stove. Once a meal has started cooking on the stove, the cook prepares the next meal on the table where the preparation time is dependent on the previous…
Piotr Dziurzański, Shuai Zhao, Leandro Soares Indrusiak
— This paper describes the possibility of applying a generic, cloud-based Optimisation as a Service facility to food cooking planning and scheduling in a commercial kitchen. We propose a chromosome encoding and customisation of the classic MOEA/D multi-objective genetic algorithm. The applicability of the proposed…
Michael J. Burns, Jonathan S. Renk, David P. Eickholt, Amanda M. Gilbert + 9 more
Lack of high throughput phenotyping systems for determining moisture content during the maize nixtamalization cooking process has led to difficulty in breeding for this trait. This study provides a high throughput, quantitative measure of kernel moisture content during nixtamalization based on NIR scanning of uncooked…
Tarini Naravane, Ilias Tagkopoulos
The future of personalized health relies on knowledge of dietary composition. The current analytical methods are impractical to scale up, and the computational methods are inadequate. We propose machine learning models to predict the nutritional profiles of cooked foods given the raw food composition and cooking…
Authors not listed
Identifying synthesis routes from knowledge graphs poses challenges beyond retrosynthesis, including path–finding artifacts and data issues. We introduce “SynGPS”, a novel algorithm that overcomes these limitations by identifying viable routes even with common artifacts. SynGPS can resolve nonsensical cycles…